There are some people that rely heavily on the statistical information provided by the media, government, and other research groups in order to form opinions or come to a conclusion on a particular idea or product. However they fail to realize that a lot of the time the data is manipulated in such a way that leads them to believe something that is not actually the case. Statistics can lie in many ways the first way is by using a sample that has a bias. For instance, the data collected would only be of one particular group of people, but they would claim it was the population. Another way data is manipulated is through averages. The data will be presented as the average, but the type of average that is taken is not given. For example is it the arithmetical average, median, or mode that is being used to present the data. This can completely skew the data one way or another. Furthermore, when data is presented the presenter can lie by leaving out certain things that will usually go unnoticed by the reader. In addition, many people make a big deal about something that doesn’t matter when using statistics, which leads the reader to believe that whatever the made a big deal about actually is significant. There could be a difference that is so tiny that it doesn’t have importance, however leaving out the range of error could also be a way of lying to the reader. The final two ways to lie with statistics are through pictures and graphs. Graphs can be easily manipulated and are easy to make someone think something that is not true. In addition, pictures can change scale and the comparison of two things could appear to be different than it actually is. Lying with statistics has lead the general public to believe several things that aren’t actually true even though the research claims that it is proven. Statistics can use a bias sample, pick a misleading average, make a big deal about something that is irrelevant, leave out key information, and manipulate graphs and pictures in order to make the audience believe something that is false.

Sampling can completely distort data and mislead the reader. The sample is supposed to represent the general population, however this is rarely the case because of the biases that lie with in sampling. For instance, the people that you interview could tend to lean towards one specific group of people. In the Yale example on page sixteen, the people that did not make a lot of money could be harder to find and interview than the rich people that have been successful. The richer people are going to be more likely to be found and answer the questionnaire, which will therefore skew the data. In addition, people could also lie about their income; some may overstate it and others could understate it. Furthermore, this was also the case in the example of the Literary Digest, their poll with regards to the election was not accurate, because the only people that they could reach to poll were the rich, because they had telephones and magazine subscriptions, and that particular group of people was biased towards the Republican Party. In many other cases, biases can be created when the person that is being interviewed is not telling the truth. We have no way of telling if the reports are from honest people. Moreover, people that are polling others could also manipulate data, because they are more likely to lean towards a certain group of people when choosing whom to give the questionnaire. There are several biases that could leave the reader to believe something that is not true. The presenter may state that the average of the general population is x, however it may only be represent able of a certain group in the general population.

Biases within sampling are not the only way people lie with statistics, they also can choose a certain type of average. Using the same data points and calculating a different average and not specify which average was used can completely...

YOU MAY ALSO FIND THESE DOCUMENTS HELPFUL

...A Synopsis of How to Lie with Statistics by Darrell Huff
When most people hear or read a statistic, they quickly have to decide if the numbers listed are valid or invalid. It is usually assumed that the author of the statistic is knowledgeable in the field to which the statistic pertains. However, on many occasions, the statistic is false, due to the author’s wording. Darrell Huff’s novelHow to Lie with Statistics is a manual that can help individuals catch these lies. The novel allows readers to solve marketing ploys and dismiss certain statistics as faulty.
The first chapter focuses on bias. The book states that all statistics are based on samples, and these samples have bias. This means that no matter what the reader will have a biased opinion. This bias is spawned from the respondents replying dishonesty, the author choosing a sample that gives better results, and the availability of data. Huff uses a survey of readership of two magazines, which had refuting results. This is because, due to the readers’ personal biases, they answered the survey dishonestly. This example closes the chapter, teaching readers to always assume that the sample has a bias. The second chapter focuses on averages. It states that there are actually three types of averages: mean, median, and mode. Mean is the arithmetic...

...How to Lie with Statistics Book Summary
The book How to Lie with Statistics written by Darrell Huff shows you howstatistics are used to mislead; sometimes unintentionally, other times on purpose. It gives the readers the knowledge necessary to intelligently question and understand the story behind the numbers. In other words, it shows the tricks the crooks use, so that honest men can use this knowledge for self defense.
I think it’s particularly useful for a manager or an executive to read and understand this book, because they are usually presented with a lot of numbers, graphs and charts and are expected to make decisions based on these numbers. People collecting and presenting the numbers to management could employ some of the tricks explained in this book and therefore, we should be careful when basing our decisions on those numbers.
It’s interesting that although this book was written in 1954, the concepts explained are just as pertinent today. Some salary figures seem to be outdated but the tricks remain pretty much the same.
The book starts with explaining the importance of sample selection and built-in bias. Sampling is critical in statistics because we can’t always count or observe every item in a population and therefore have to base our judgments on a selected sample. However, a sample with a built-in bias could...

...sound good.
Keep in mind that a statistic is only worthwhile when it satisfies the assumptions on the test. Knowing whether the assumptions are met is dependent on the competence of the person running the test.
Just because two things seem to have a relationship, could it have been by pure chance? It cannot be determined by causation and effect. The two variables have no effect on each other at all.
Chapter 9 – How to Statisticulate
Statisticulate is the process of misleading people using statistics. It is also misinforming with figures, or statistical manipulation might not be a mathematician purpose.
Lying with statistics – is this dishonesty or incompetence? Mostly dishonesty.
The author list various tricks – things like measuring profit on cost price, showing a graph with a finer Y-axis scale just to show the steep growth is, how income calculations mislead by involving children in the family as individuals for the average amongst a few.
Chapter 10 – How to Talk Back to a Statistic
In how we talk back to a statistic one should ask themselves to find out if the statistic that you are reading being presented is it genuine or not.
There are 5 simple steps, in Huff’s own words, “how to look a phoney statistic in the eye and face it down”. (page **)
Question 1 – Who says so?
Find...

...How to Lie with Statistics” by Darrell Huff was a great book to read for a student like myself that is entering a course in statistics. It gave me the insight that I needed to know what statistics is all about and even the ‘tricks’ about using statistics that I can use when I get older and maybe have an important business job for example were I must present for the company and this book proves to be my savior. Though anyway it’s still very influential. This book wasn’t very hard to get through and it gave me a new outlook on statistics that I definitely didn’t have prior to my reading it.
Before I may have had my own interpretation of statistics, but Huff has shaped my understanding into something much better than it was before. Something that the book was big on was common error in statistics that a lot of people come a crossed. And something that I learned is that these errors are not always unintentional. Sometimes, in fact, they can actually be intentionally done. Huff shows us how some of the simple ideas such as averages are
manipulated to be more appealing to the viewer. Even how the mode can be the most frequently observed outcome even though it is rarely reported with numeric data.
One of the biggest ideas shown in the book to my opinion was how he explained the power of the graph....

...Professor Dumonceaux
Descriptive Statistics Paper
2 June 2014
Finding a New Home
According to Trochim, “Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data” (Trochim, 2006). For many years, many studies and researches have been done in real estate market. Buyers need to conduct researches to decide which house they will purchase. Buyers’ concerns include the price of the house, the number of bedrooms, and location. Real estate agents need to gather all the necessary information to provide their services to buyers. Additionally, the agents must be able to predict what types of houses are most likely to sell. In this paper, I will provide the summary of what I have been studying. The paper will include the measure of central tendency, dispersion, and skew for data. In addition, this paper will also contain graphic data as well as tabular data to demonstrate my findings and studies. In the end, conclusion will present whether my research findings answered the problem statement or if more research may be needed.
Examining the data collected for the current real estate market desires, following are the conclusions based on its findings. There are many key factors to consider when purchasing a home. Some of the factors include interest...

...scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptive statistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some generality.
In Chapter 4 we discuss statistical inference (estimation), where the basic problem is to estimate
one or more characteristics of a population. Since it is too expensive to obtain the population
information, we instead select a sample from the population and then use the information in the
sample to infer the characteristics of the population.
In Chapter 5 we look at the topic of regression analysis which is used to study relationships
between variables.
In Chapter 6 we study another type of decision making called decision analysis where costs and
proﬁts are considered to be important. The problem is not whether to accept or reject a statement
but to select the best alternative from a list of several possible decisions. Usually no statistical
data are available. Decision analysis is the study of how people make decisions, particularly
when faced with imperfect information or uncertainty....

...﻿Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times something happens. As I examined on what the statement says, the phrase “number of times something happens” really caught my attention because my subconscious says “here we go again the non-stop solving, analyzing of problems” and I was right. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it. At first I thought that I will be alright all along with this subject but it seems that just some part of it maybe it is because I don’t pay much of my attention to it but I have learned many things. I have learned my lesson.
During our every session in this subject before having our midterm examination I really had hard and bad times in coping up with this subject. When we have our very first quiz I thought that I would fail it but it did not happen but after that, my next quizzes I have taken I failed. I was always feeling down when in every quiz I failed because even though I don’t...

...of 1000 flights and proportions of three routes in the sample. He divides them into different sub-groups such as satisfaction, refreshments and departure time and then selects proportionally to highlight specific subgroup within the population. The reasons why Mr Kwok used this sampling method are that the cost per observation in the survey may be reduced and it also enables to increase the accuracy at a given cost.
TABLE 1: Data Summaries of Three Routes
Route 1
Route 2
Route 3
Normal(88.532,5.07943)
Normal(97.1033,5.04488)
Normal(107.15,5.15367)
Summary Statistics
Mean
88.532
Std Dev
5.0794269
Std Err Mean
0.2271589
Upper 95% Mean
88.978306
Lower 95% Mean
88.085694
N
500
Sum
44266
Summary Statistics
Mean
97.103333
Std Dev
5.0448811
Std Err Mean
0.2912663
Upper 95% Mean
97.676525
Lower 95% Mean
96.530142
N
300
Sum
29131
Summary Statistics
Mean
107.15
Std Dev
5.1536687
Std Err Mean
0.3644194
Upper 95% Mean
107.86862
Lower 95% Mean
106.43138
N
200
Sum
21430
From the table above, the total number of passengers for route 1 is 44,266, route 2 is 29,131 and route 3 is 21,430 and the total numbers of passengers for 3 routes are 94,827.
Although route 1 has the highest number of passengers and flights but it has the lowest means of passengers among the 3 routes. From...